US9002097B1 - Method and system for enhancing image quality - Google Patents
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- US9002097B1 US9002097B1 US13/776,939 US201313776939A US9002097B1 US 9002097 B1 US9002097 B1 US 9002097B1 US 201313776939 A US201313776939 A US 201313776939A US 9002097 B1 US9002097 B1 US 9002097B1
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Definitions
- the present invention relates to a method for enhancing image quality scanned by using an inspection tool.
- Defect inspection systems frequently utilize charged particle beams.
- a charged particle beam such as an electron beam (e-beam)
- e-beam electron beam
- the interaction of the electron beam with the inspected surface generates secondary electron signals, which is collected as grayscale images, and which are compared to detect defect by observing the change in gray scale.
- the e-beam inspection typically use multi-scans, i.e., repeated scans, for a same sample to obtain low noise image.
- the scan times may be reduced or limited to lower the cost, but image quality would be a critical concern. Deteriorated image quality may ignore small defect and increase the false rate on defect determination, causes alignment error in the following alignment process, and even result in the devices to fail. As the dimensions of semiconductor devices decrease, inspection becomes even more important and image quality should be promoted.
- Median filter is a nonlinear digital filtering technique used to remove noise.
- the main idea of the median filter is to run through the signal entry by entry, replacing each entry with the median of neighboring entries.
- a pixel with its neighbor can form a matrix, and a median value can be determined from this matrix to replace the possible extreme value of this pixel.
- the median filter is not suitable for the defect inspection systems. If a defect happens to one pixel only, this defect will be ignored by the median filter. In addition, larger image distortion occurs when tuning brightness and contrast.
- An object of this invention is to provide methods or systems for enhancing the image quality, thereby saving time and cost.
- An embodiment of this invention provides a method for enhancing image quality, comprising the steps of: recording a sequence of grayscales of a pixel scanned by a charged particle beam; removing extreme values from the sequence of grayscales and remaining other grayscales; and determining a nominated grey level of the pixel from the remained grayscales.
- Another embodiment of this invention provides a system for enhancing image quality, comprising: means for recording a sequence of grayscales of a pixel scanned by a charged particle beam; means for removing extreme values from the sequence of grayscales and remaining other grayscales; and means for calculating an average or a median of the remained grayscales to obtain an nominated grayscale of the pixel.
- Another embodiment of this invention provides a method for enhancing image quality, comprising: scanning a specimen to obtain a plurality of frames by using a charged particle beam; removing extreme grayscales of each pixel of the plurality of frames; and averaging remained grayscales of each pixel of the plurality of frames to obtain a scanned image of the specimen.
- FIG. 1 shows a method for enhancing image contrast according to an embodiment of this invention.
- FIG. 2 shows recorded eight scanned grayscales with time information of a particular pixel.
- FIG. 3A shows an example for discarding the extreme grayscales.
- FIG. 3B shows a particular example of FIG. 3A .
- FIG. 3C shows another particular example of FIG. 3A .
- FIG. 4 shows an example in which a pie chart is used to check whether the discarded grayscales correlate with the time of scan.
- FIG. 5 shows an example of FIG. 1 .
- FIG. 6 shows an inspection system 6 according to an embodiment of this invention.
- FIG. 7 is a flowchart showing the process of the inspection system according to an embodiment of this invention.
- This invention is directed to methods and systems for improving image quality of frames obtained from an inspection system.
- the inspection system repeatedly inspects a sample, and the inspected frames for the same sample are processed to obtain an improved image.
- a cherry-pick method is employed to remove noises or values of the frames.
- the term “cherry-pick” refers to employing an automatic or manual way, or an arbitrary or rational rule, to pick out the unwanted noises or values.
- the inspection system may be an optical inspection system, or an inspection system using a charged particle beam.
- embodiments of this invention employ the cherry-pick method to treat frames obtained from insufficient quantity of inspection times. For frames obtained from many inspection times, e.g., 100 times, the cherry-pick method may be unnecessary because the noises may contribute little weight in such cases.
- the cherry-pick method is employed to treat frames obtained from limited inspection times, e.g., 4 or 10 times. Noises contribute big weight in such cases and they have to be removed.
- the inspection system uses a charged particle beam to inspect the sample.
- Systems capable of irradiating a charged particle beam can be employed by this invention.
- the charged particle beam interacts with the sample and signals are thus generated and collected as grayscale frames.
- the inspection system using the charged particle beam has the advantage of high resolution.
- the inspection system is a point-to-point imaging system, such as a scanning electron microscope (SEM), a focused ion beam (FIB), or an atomic force microscope (AFM) inspection system.
- SEM scanning electron microscope
- FIB focused ion beam
- AFM atomic force microscope
- FIG. 1 shows a method for enhancing image quality according to an embodiment of this invention.
- Step 10 a sequence of grayscales of a pixel scanned by a charged particle beam is recorded.
- the method may employ a defect invention system emitting electron beams to repeatedly scan a specimen in time sequence.
- the specimen may comprise a wafer, such as a silicon wafer, or a mask, such as an extreme ultraviolet mask.
- the times of multi-scan may range from several to tens. For example, a 12 inch wafer is scanned for 8 times and eight frames are obtain, in which grayscales of each pixel of each frame incorporated with time information are recorded.
- FIG. 2 shows the recorded eight scanned grayscales with time information of a particular pixel.
- step 20 some of the recorded grayscales are removed from the sequence, and other grayscales are remained.
- the method of this invention may employ a statistic manner to remove extreme values from the recorded sequence of grayscales.
- the recorded grayscales may be firstly analyzed to identify its distribution by statistic charts, such as histogram, or other methods know in the art.
- an upper limit and a lower limit may be defined to remove the abnormal extreme values.
- the extreme grayscales may be due to the apparatus for emitting the charged particle beam, or due to accumulated charge in the scanned surface.
- FIG. 3A shows an example for discarding the extreme grayscales.
- the distribution of the recorded grayscales is a standard normal distribution with a mean ⁇ and a standard deviation ⁇ .
- the area under the normal curve within 0.67 standard deviation of the mean is about 50% of the total area under the curve.
- the area under the normal curve within 1.28 standard deviation of the mean is about 80% of the total area under the curve.
- the extreme values are defined as the highest 25% and lowest 25% of the recorded sequence of grayscales. For example, the specimen is repeatedly scanned for four times and each pixel has four grayscales. According to the definition, the maximum and the minimum of the four will be discarded. In another embodiment, the extreme values are defined as the highest 10% and lowest 10% of the recorded sequence of grayscales.
- some embodiment cherry-picks the recorded sequence of grayscales, picking up grayscales only within suitable range regardless whatever distributions.
- An error diagnose may be made before removing the extreme grayscales and the extreme values may be accordingly defined.
- the recorded sequence of grayscales incorporated with time information, as well as the parameters of scans, may provide useful information to spot the source of the noise.
- the diagnose may use various statistical charts.
- FIG. 4 shows an example in which a pie chart is used to check whether the discarded grayscales correlate with the time of scan.
- the probability of each scan should be almost the same and about 25% in theory.
- extreme grayscales may be changed after the error diagnose. For example, in the four-times scan shown in the last paragraph, it is diagnosed that the grayscales are deviated to high due to a problem of inspection system. In this case, the largest two grayscales may be defined as the extreme grayscales. In the contrary, if engineers diagnose that the grayscales are deviated to low due to another problem of inspection system, the smallest two grayscales may be defined as the extreme grayscales.
- control charts may be employed to assist the error diagnose.
- the control charts should be carefully used because there may be absence of a target value for the charged particle beam inspection.
- a statistic method is employed to determine a nominated grayscale of the pixel from the remained grayscales.
- the remained grayscales are averaged and the average value is used to denote the pixel, i.e., as the nominated grayscale of the pixel.
- the median of the remained grayscales is used to denote the pixel.
- the nominated grayscale is determined by other statistical methods except the average and median method.
- the remained grayscales may be manipulated through other methods to denote the pixel.
- FIG. 5 shows an example of FIG. 1 .
- a eight-times scan in time sequence is performed to an extreme ultraviolet mask, and eight grayscales of each pixel are stored in which step 10 shows eight grayscales of a pixel, i.e., 210 , 165 , 163 , 163 , 162 , 161 , 160 , and 154 .
- step 20 the maximum and the minimum grayscale of the eight, i.e., 210 and 154 , are automatically removed due to out of the upper and lower limits or for other reasons, and other six grayscales are remained.
- the average or the median of the remained six grayscales is calculated to be the nominated grayscale of the pixel, which is 162.33 for the average or 162.5 for the median.
- Another embodiment of this invention provides a system for enhancing image quality, which comprises: means for recording a sequence of grayscales of a pixel scanned by a charged particle beam; means for removing extreme values from the sequence of grayscales and remaining other grayscales of the sequence of grayscales; and means for determining a nominated grayscale of the pixel from the remained grayscales.
- the system is configured to store image data generated by scanning a wafer or a mask, such as a silicon wafer or an extreme ultraviolet (EUV) mask.
- the system may comprises one or more processors coupled to a detector, and each processor receives a portion of image data generated by the detector during scanning.
- the system further comprises an array of storage media, such as a memory cell, separately coupled to each processor, storing all of the image data sent by each processor.
- the one or more processors may be responsible for removing the extreme values and determining the nominated grayscale, which have been descried in the foregoing paragraphs.
- Another embodiment of this invention provides a computer readable medium encoded with a computer program for enhancing image quality of frames obtained from the inspection system.
- the computer readable medium primarily comprises the steps of: recording a sequence of grayscales of a pixel scanned by a charged particle beam; removing extreme values from the sequence of grayscales and remaining other grayscales; and determining a nominated grey level of the pixel from the remained grayscales.
- FIG. 6 shows an inspection system 6 according to an embodiment of this invention.
- a sample 70 such as a wafer or a mask, is loaded on a sample stage 68 to be inspected.
- a charged particle beam generator 61 generates a primary charged particle beam 601 , preferably an electron beam.
- a condenser lens module 62 condenses the primary charged particle beam 601 .
- a probe forming objective lens module 63 focuses the condensed primary charged particle beam into a charged particle beam probe 602 .
- a charged particle beam deflection module 64 deflects the formed charged particle beam probe 602 to the surface of the sample 70 . Secondary charged particles 603 are emitted from the surface of the sample 70 bombarded by the charged particle beam probe 602 .
- a secondary charged particle detector module 65 detects the secondary charged particles 603 and generates a secondary charged particle detection signal 604 .
- An image forming module 66 communicated with the secondary charged particle detector module 65 receives the secondary charged particle detection signal 604 and forms one or more frames.
- the image forming module 66 may be a host, a terminal, a personal computer, or the like.
- a noise-filtering module 67 communicated with the image-forming module 66 treats the scanned frames by methods mentioned in the foregoing embodiments, so as to obtain a image with improved quality.
- noise-filtering module may comprise the above-mentioned processers and memories for storing and processing the image and inspection data of the frames.
- the connection between the image forming module 66 and the secondary charged particle detector module 65 may be wire or wireless manners known in the art.
- FIG. 7 is a flowchart showing the process of the inspection system according to an embodiment of this invention.
- the inspection system performs a multi-scan to a sample.
- the results of the multi-scan are treated by the method, particularly the cherry-pick method of this invention.
- Step 703 after image-processing, an image with improved quality can be obtained.
- Step 704 in the meantime, the image-processing method analyzes the scanned frames to check the condition of the inspection system. For example, the method may check whether a system error is presented.
- Step 705 the defects of the sample can be determined by the improved image.
- each pixel By cherry-picking the recorded sequence of grayscales, each pixel obtains a nominated grayscale with reduced noise.
- the signal-to-noise ratio of the scanned image is increased and better image quality is hence obtained.
- the qualified good image quality promotes the accuracy of the alignment process, increase defect-detecting sensitivity, and decrease defect false rate. Accordingly, embodiments of this invention provide methods and system can significantly reduce the inspection time and cost.
Abstract
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